Why is replay testing necessary for Temporal workflows?

Replay testing ensures that your workflow code remains deterministic. It validates that updated code can still successfully process existing event histories from production without throwing non-deterministic errors.

How does time-skipping work in Temporal Python testing?

Time-skipping uses a specialized WorkflowEnvironment that automatically advances the clock when a workflow is blocked on a timer or sleep, allowing tests for long-running processes to complete in milliseconds.

Can I test activities in isolation without a full workflow?

Yes, this skill provides patterns using Temporal's ActivityEnvironment to run and test activities individually, allowing you to mock inputs and verify outputs in a controlled environment.

What is the recommended test coverage for Temporal projects?

A target of ≥80% logic coverage is recommended for both workflows and activities to ensure critical paths and error handling scenarios are fully validated before deployment.

Temporal Python Testing

Name: Temporal Python Testing
Author: HermeticOrmus

byHermeticOrmus

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보안 및 테스팅

Streamlines Temporal workflow testing in Python through automated time-skipping, activity mocking, and determinism validation.

소개

This skill equips developers with a comprehensive framework for testing Temporal workflows using the Python SDK and pytest. It addresses the unique challenges of testing distributed stateful systems by providing standardized patterns for time-skipping long-running workflows, mocking external activities for isolated unit tests, and performing replay testing to ensure code changes maintain determinism. By integrating these strategies, developers can achieve high test coverage and ensure production reliability for complex orchestration logic.

주요 기능

Advanced activity mocking and environment simulation using ActivityEnvironment
Determinism validation via production history replay testing
Automated time-skipping for fast execution of long-running workflows
Pre-configured pytest fixtures for rapid local development setup
CI/CD integration patterns for automated testing pipelines
2 GitHub stars

사용 사례

Testing month-long subscription or trial workflows in seconds
Validating workflow determinism before deploying code changes to production
Mocking external API dependencies to isolate workflow logic during integration tests

소개

주요 기능

Advanced activity mocking and environment simulation using ActivityEnvironment
Determinism validation via production history replay testing
Automated time-skipping for fast execution of long-running workflows
Pre-configured pytest fixtures for rapid local development setup
CI/CD integration patterns for automated testing pipelines
2 GitHub stars

사용 사례

Testing month-long subscription or trial workflows in seconds
Validating workflow determinism before deploying code changes to production
Mocking external API dependencies to isolate workflow logic during integration tests